package com.zgl.hadoop.configuration.common;

import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.scheduling.annotation.EnableAsync;
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;

import java.util.concurrent.Executor;
import java.util.concurrent.ThreadPoolExecutor;

/**
 * \* Created with IntelliJ IDEA.
 * \* User: zgl
 * \* Date: 2018-10-11
 * \* Time: 17:19
 * \* To change this template use File | Settings | File Templates.
 * \* Description:
 * \
 */
@Configuration
@EnableAsync
public class ThreadPool {
//    @Value("${threadPool.corePoolSize}")
    private int corePoolSize = 10;//线程池维护线程的最少数量
//    @Value("${threadPool.maxPoolSize}")
    private int maxPoolSize = 30;//线程池维护线程的最大数量
//    @Value("${threadPool.queueCapacity}")
    private int queueCapacity = 60;//缓存队列
//    @Value("${threadPool.keepAlive}")
    private int keepAlive = 60;//允许的空闲时间
//    @Value("${threadPool.timeout}")
    private int timeout = 10;// 等待线程池任务执行结束超时时间

    @Bean
    public Executor myExecutor() {
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
        executor.setCorePoolSize(corePoolSize);
        executor.setMaxPoolSize(maxPoolSize);
        executor.setQueueCapacity(queueCapacity);
        executor.setThreadNamePrefix("mqExecutor-");
        //rejection-policy：当pool已经达到max size的时候，如何处理新任务
        //CALLER_RUNS：不在新线程中执行任务，而是由调用者所在的线程来执行
        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy()); //对拒绝task的处理策略
        executor.setKeepAliveSeconds(keepAlive);
        executor.setAwaitTerminationSeconds(timeout);
        executor.initialize();
        return executor;
    }


}
